• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.267-268
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• 2007

A dynamic range compression algorithm using Markov random field (MRF) modeling to display high dynamic range (HDR) images on low dynamic range (LDR) devices is proposed in this work. The proposed algorithm separates foreground objects from the background using the edge information, and then compresses the color differences across the edges based on the MRF modeling. By minimizing a cost function using belief propagation, the proposed algorithm can provide an effective LDR image. Simulation results show that the proposed algorithm provides good results.

• 한국멀티미디어학회논문지
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• 제19권11호
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• pp.1900-1908
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• 2016

Recent times have seen the introduction of modeling technologies using implicit surface and marching cubes algorithm in the field of computer graphics. Implicit surface modeling is used to express characters or fluid. This study presents a calculation method for the density of curve skeletal primitives using parametric curve and implements an implicit surface modeling tool by utilizing Maya API. Skeletal primitives can be assembled and utilized in character modeling using the implemented modeling tool. Results could be obtained more effectively compared to existing particle-based methods.

• 한국CDE학회논문집
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• 제5권4호
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• pp.293-300
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• 2000

The non-manifold geometric modeling technique is to improve design process and to Integrate design, analysis, and manufacturing by handling mixture of wireframe model, surface model, and solid model in a single data structure. For the non-manifold geometric modeling, Euler operators and other high level modeling methods are necessary. Boolean operation is one of the representative modeling method for the non-manifold geometric modeling. This thesis studies Boolean operations of non-manifold model with the data structure of selective storage. The data structure of selective storage is improved non-manifold data structure in that existing non-manifold data structures using ordered topological representation method always store non-manifold information even if edges and vortices are in the manifold situation. To implement Boolean operations for non-manifold model, intersection algorithm for topological cells of three different dimensions, merging and selection algorithm for three dimensional model, and Open Inventor(tm), a 3D toolkit from SGI, are used.

• 제어로봇시스템학회논문지
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• 제10권5호
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• 지구물리와물리탐사
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• 제2권2호
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• pp.86-95
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• 1999

이 연구에서는 적분방정식의 근사해를 이용한 3차원 모델링 알고리듬을 구성하고 그 효율성을 분석하였다. 전기장 적분방정식에 확장 Born 근사(extended Born approximation)를 적용시켜 알고리듬을 구성하였으며 모델링의 계산 속도를 향상시키기 위하여 Green 텐서 적분을 공간 주파수 영역에서 수행하였다. 이 방법은 연속 함수로 표현되는 전기전도도를 갖는 이상체에 대한 모델 계산을 가능하게 하고, Green 텐서 적분시 발생하는 특이치 문제가 발생하지 않는 장점이 있다 얇은 전도체에 대한 모델링 계산 결과를 적분방정식의 해와 비교하여 알고리듬의 타당성을 검증하였다. 전기전도도 물성차, 사용 송신원의 주파수에 따른 개발된 알고리듬의 분석을 통하여 물성차 1:16 정도, 사용주파수는 100 Hz-100 kHz까지 정확한 결과를 얻었다. 그러나, 확장 Born 근사는 송신원과 모델의 상대적인 위치에 따라 오차를 나타내었다. 한편, 연속적인 전기전도도 함수를 갖는 모델에 대한 이 알고리듬의 적용성를 알아보기 위하여 서로 다른 전기전도도를 갖는 두 이상체가 접합한 모델에 대하여 적분방정식의 해와 비교하였으며 양호한 결과를 나타내었다.

• 지구물리와물리탐사
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• 제18권4호
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• pp.232-240
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• 2015

자연 전자기장을 이용하여 지하 매질의 전기적 구조를 규명하는 자기지전류(magnetotelluric; MT) 탐사의 정확한 해석을 위해서는 특정 전기적 구조에 대한 정확한 수치적 반응을 구할 수 있는 3차원 모델링이 필수적이다. 특히, 매질내에 전기적 이방성이 있을 때는 MT 반응이 달라지므로 전기적 이방성의 영향을 고려한 MT 탐사 모델링이 필요하다. 특히, MT 탐사기법을 이용한 지열저류층의 모니터링과 같이 MT 반응의 작은 변화를 분석해야 하는 시간경과 자료의 해석의 경우, 대상 지역에 이방성이 존재할 경우 이를 고려할 수 있는 정확한 모델링이 필수적이다. 이 연구에서는 기존의 등방성만을 고려하던 유한차분법 MT 모델링 알고리듬을 수직 혹은 수평 횡등방성 이방성을 고려할 수 있도록 개선하였다. 개발한 알고리듬을 박리층 모델을 이용하여 검증한 후, 수직횡등방성 이방성이 MT 반응에 미치는 영향에 대해서 분석하였다. 향후에는 수평 횡등방성 이방성이 MT 반응에 미치는 영향에 대해서도 분석하고자 하며, 알고리듬을 더욱 발전시켜 경사 횡등방성 이방성까지 고려할 수 있도록 발전시키고자 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1254-1259
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권2호
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• pp.95-101
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권3호
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.283-287
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• 1996

The exhaust noise reduction of automobile with the active muffler is experimentally investigated. The control algorithm is the filtered-x LMS algorithm and the inverse algorithm with the adaptive line enhancer. Also, the control efficiency is increased with synthesized second harmonic engine frequency. In the experiment, the active muffler is applied to the end of exhaust system in automobile and the control with on-line secondary path modeling method(inverse algorithm) is compared the control of off-line secondary path modeling method. As secondary path transfer functions are changed, the experimental results show that the control performance with on-line method is more efficient than that with off-line method in the exhaust noise reduction of automobile.